Generalized energy and gradient flow via graph framelets. - Andi Han; Dai Shi; Zhiqi Shao; Junbin Gao (CoRR, 2022)

Generalized Laplacian Regularized Framelet GCNs. - Zhiqi Shao; Andi Han; Dai Shi; Andrey Vasnev; Junbin Gao (CoRR, 2022)

A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models. - Dai Shi; Zhiqi Shao; Andi Han; Yi Guo 001; Junbin Gao (ACML, 2023)

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion. - Dai Shi; Zhiqi Shao; Yi Guo 001; Qibin Zhao; Junbin Gao (CoRR, 2023)

Frameless Graph Knowledge Distillation. - Dai Shi; Zhiqi Shao; Yi Guo 001; Junbin Gao (CoRR, 2023)

How Curvature Enhance the Adaptation Power of Framelet GCNs. - Dai Shi; Yi Guo 001; Zhiqi Shao; Junbin Gao (CoRR, 2023)

Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond. - Zhiqi Shao; Dai Shi; Andi Han; Yi Guo 001; Qibin Zhao; Junbin Gao (CoRR, 2023)

CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model. - Zhiqi Shao; Michael G. H. Bell; Ze Wang; D. Glenn Geers; Xusheng Yao; Junbin Gao (CoRR, 2024)

ST-SSMs: Spatial-Temporal Selective State of Space Model for Traffic Forecasting. - Zhiqi Shao; Michael G. H. Bell; Ze Wang; D. Glenn Geers; Haoning Xi; Junbin Gao (CoRR, 2024)

ST-MambaSync: The Confluence of Mamba Structure and Spatio-Temporal Transformers for Precipitous Traffic Prediction. - Zhiqi Shao; Xusheng Yao; Ze Wang; Junbin Gao (CoRR, 2024)

STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting. - Zhiqi Shao; Haoning Xi; Haohui Lu; Ze Wang; Michael G. H. Bell; Junbin Gao (CoRR, 2024)

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion. - Dai Shi; Zhiqi Shao; Yi Guo 001; Qibin Zhao; Junbin Gao (Trans. Mach. Learn. Res., 2024)

Enhancing framelet GCNs with generalized p-Laplacian regularization. - Zhiqi Shao; Dai Shi; Andi Han; Andrey Vasnev; Yi Guo 001; Junbin Gao (Int. J. Mach. Learn. Cybern., 2024)

Revisiting time-varying dynamics in stock market forecasting: A multi-source sentiment analysis approach with large language model. - Zhiqi Shao; Xusheng Yao; Feng Chen 008; Ze Wang; Junbin Gao (Decis. Support Syst., 2025)

ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial-temporal traffic forecasting. - Zhiqi Shao; Ze Wang; Xusheng Yao; Michael G. H. Bell; Junbin Gao (Inf. Fusion, 2025)

Frameless Graph Knowledge Distillation. - Dai Shi; Zhiqi Shao; Junbin Gao; Zhiyong Wang 001; Yi Guo 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)